added a file to sandbox

Author: Takeshi Ikuma (LSUHSC)

sandbox/so78714317.py

@@ -0,0 +1,159 @@
+import logging
+logging.basicConfig(level=logging.DEBUG)
+
+# import serial
+import matplotlib.pyplot as plt
+
+# from matplotlib.animation import FuncAnimation, FFMpegWriter
+import ffmpegio as ff
+
+from datetime import datetime, timedelta
+import numpy as np
+import schedule
+import time
+
+# Constants
+GRAVITY = 9.81  # Standard gravity in m/s²
+
+# Initialize serial connections to HC-06 devices
+# ser_x_accel = serial.Serial('COM4', 9600, timeout=1)  # X-axis acceleration data
+# ser_y_angle = serial.Serial('COM11', 9600, timeout=1)  # Y-axis angle data
+
+# Initialize empty lists to store data
+x_accel_data = []
+y_angle_data = []
+timestamps = []
+
+# Initialize Excel workbook
+# wb = openpyxl.Workbook()
+# ws = wb.active
+# ws.title = "Sensor Data"
+# ws.append(["Timestamp", "X Acceleration (m/s²)", "Y Angle (degrees)"])
+
+
+# Function to update the plot and log data
+def update(f):
+    # Read data from serial connections
+    line_x_accel = np.random.randn(1)  # ser_x_accel.readline().decode('utf-8').strip()
+    line_y_angle = np.random.randn(1)  # ser_y_angle.readline().decode('utf-8').strip()
+
+    try:
+        # Parse and process X-axis acceleration data
+        x_accel_g = float(line_x_accel)  # Acceleration in g read from serial
+        x_accel_ms2 = x_accel_g * GRAVITY  # Convert from g to m/s²
+        x_accel_data.append(x_accel_ms2)
+
+        # Parse and process Y-axis angle data
+        y_angle = float(line_y_angle)
+        y_angle_data.append(y_angle)
+
+        # Append timestamp
+        timestamps.append(datetime.now())
+
+        # Limit data points to show only the latest 100
+        if len(x_accel_data) > 100:
+            x_accel_data.pop(0)
+            y_angle_data.pop(0)
+            timestamps.pop(0)
+
+        # Log data to Excel with timestamp
+        # timestamp_str = timestamps[-1].strftime("%H:%M:%S")
+        # ws.append([timestamp_str, x_accel_data[-1], y_angle_data[-1]])
+
+        # Clear and update plots
+        ax1.clear()
+        ax1.plot(timestamps, x_accel_data, label="X Acceleration", color="b")
+        ax1.legend(loc="upper left")
+        ax1.set_ylim([-20, 20])  # Adjust based on expected acceleration range in m/s²
+        ax1.set_title("Real-time X Acceleration Data")
+        ax1.set_xlabel("Time")
+        ax1.set_ylabel("Acceleration (m/s²)")
+        ax1.grid(True)
+
+        ax2.clear()
+        ax2.plot(timestamps, y_angle_data, label="Y Angle", color="g")
+        ax2.legend(loc="upper left")
+        ax2.set_ylim([-180, 180])
+        ax2.set_title("Real-time Y Angle Data")
+        ax2.set_xlabel("Time")
+        ax2.set_ylabel("Angle (degrees)")
+        ax2.grid(True)
+
+        # Update text boxes with latest values
+        text_box.set_text(f"X Acceleration: {x_accel_data[-1]:.2f} m/s²")
+        text_box2.set_text(f"Y Angle: {y_angle_data[-1]:.2f}°")
+
+        # Save the workbook periodically (every 100 updates)
+        # if frame % 100 == 0:
+        # wb.save("sensor_data.xlsx")
+
+        # plt.draw()
+
+        # print("update", datetime.now())
+        f.write(fig)
+
+    except ValueError:
+        pass  # Ignore lines that are not properly formatted
+
+
+# Setup the plots
+# with plt.ion():
+fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8))
+text_box = ax1.text(
+    0.05,
+    0.95,
+    "",
+    transform=ax1.transAxes,
+    fontsize=12,
+    verticalalignment="top",
+    bbox=dict(boxstyle="round", facecolor="wheat", alpha=0.5),
+)
+text_box2 = ax2.text(
+    0.05,
+    0.95,
+    "",
+    transform=ax2.transAxes,
+    fontsize=12,
+    verticalalignment="top",
+    bbox=dict(boxstyle="round", facecolor="wheat", alpha=0.5),
+)
+
+with ff.open(
+    "sandbox/test.mp4|[f=mpegts]udp://127.0.0.1:1234?pkt_size=1316",
+    "wv",
+    rate_in=10,
+    y=ff.FLAG,
+    show_log=True,
+    preset="ultrafast",
+    tune="zerolatency",
+    vcodec="libx264",
+    map= '0:v',
+    f="tee",
+) as f:
+    s = schedule.every(0.1)
+    s.seconds.until(datetime.now() + timedelta(seconds=10)).do(
+        update, f
+    )  # minutes=1)
+
+    while True:
+        n = schedule.idle_seconds()
+        if n is None:
+            # no more jobs
+            break
+        elif n > 0:
+            # sleep exactly the right amount of time
+            time.sleep(n)
+        schedule.run_pending()
+        time.sleep(0.1)
+
+    print("schedule complete")
+
+# # Animate the plots
+# ani = FuncAnimation(fig, update, interval=100)  # Update interval of 100ms
+
+# # Save the animation as a video file
+# writer = FFMpegWriter(fps=10, metadata=dict(artist='Me'), bitrate=1800)
+# ani.save("sensor_data.mp4", writer=writer)
+
+# plt.tight_layout()
+# plt.show()